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— retrieve rows from a table or view


[ WITH [ RECURSIVE ] <with_query> [, ...] ]
SELECT [ ALL | DISTINCT [ ON ( <expression> [, ...] ) ] ]
[ * | <expression> [ [ AS ] <output_name> ] [, ...] ]
[ FROM <from_item> [, ...] ]
[ WHERE <condition> ]
[ GROUP BY <grouping_element> [, ...] ]
[ HAVING <condition> [, ...] ]
[ WINDOW <window_name> AS ( <window_definition> ) [, ...] ]
[ { UNION | INTERSECT | EXCEPT } [ ALL | DISTINCT ] <select> ]
[ ORDER BY <expression> [ ASC | DESC ] [ NULLS { FIRST | LAST } ] [, ...] ]
[ LIMIT { <count> | ALL } ]
[ OFFSET <start> [ ROW | ROWS ] ]
[ FETCH { <FIRST> | <NEXT> } [ <count> ] { ROW | ROWS } { ONLY | WITH TIES } ];

where with_query is:

<with_query_name> [ ( <column_name> [, ...] ) ] AS ( <select> )

and from_item can be one of:

<table_name> [ [ AS ] <alias> [ ( <column_alias> [, ...] ) ] ]
[ TABLESAMPLE <sampling_method> ( <sample_size> ) [ REPEATABLE ( <seed> ) ] ]

<with_query_name> [ [ AS ] <alias> [ ( <column_alias> [, ...] ) ] ]

[ LATERAL ] ( <select> ) [ AS ] [<alias>] [ ( <column_alias> [, ...] ) ]

[ LATERAL ] <function_name> ( [ <argument> [, ...] ] )
[ [ AS ] <alias> [ ( <column_alias> [, ...] ) ] ]

<from_item> [ NATURAL ] <join_type> <from_item>
[ ON <join_condition> | USING ( <join_column> [, ...] )

and grouping_element can be one of

( )
( <expression>s [, ...] )
ROLLUP ( { <expression> | ( <expression> [, ...] ) } [, ...] )
CUBE ( { <expression> | ( <expression> [, ...] ) } [, ...] )
GROUPING SETS ( <grouping_element> [, ...] )

and sample_size can be one of:

<size> [ ROWS | PERCENT ]
<size> PERCENT [ BETWEEN { <count> | UNBOUNDED } ROWS AND { <count> | UNBOUNDED } ROWS }


SELECT retrieves rows from zero or more tables. The general processing of SELECT is as follows:

  1. The queries in the WITH list effectively serve as temporary tables that can be referenced in the FROM list. A WITH query that is referenced more than once in FROM is computed only once. See WITH Clause below.

  2. All elements in the FROM list are computed. If more than one element is specified in the FROM list, they are cross-joined together. See FROM Clause below.

  3. If the WHERE clause is specified, all rows that do not satisfy the condition are eliminated from the output. See WHERE Clause below.

  4. If the GROUP BY clause is specified, or if there are aggregate function calls, the output is combined into groups of rows that match on one or more values, and the results of aggregate functions are computed. If the HAVING clause is present, it eliminates groups that do not satisfy the given condition. See GROUP BY Clause and HAVING Clause below.

  5. The actual output rows are computed using the SELECT output expressions for each selected row or row group. See SELECT List below.

  6. SELECT DISTINCT eliminates duplicate rows from the result. SELECT DISTINCT ON eliminates rows that match on all the specified expressions. SELECT ALL (the default) will return all candidate rows, including duplicates. See DISTINCT Clause below.

  7. Using the operators UNION, INTERSECT, and EXCEPT, the output of more than one SELECT statement can be combined to form a single result set. The UNION operator returns all rows that are in one or both of the result sets. The INTERSECT operator returns all rows that are strictly in both result sets. The EXCEPT operator returns the rows that are in the first result set but not in the second. In all three cases, duplicate rows are eliminated unless ALL is specified. The noise word DISTINCT can be added to explicitly specify eliminating duplicate rows. Notice that DISTINCT is the default behavior here, even though ALL is the default for SELECT itself. See UNION Clause, INTERSECT Clause, and EXCEPT Clause below.

  8. If the ORDER BY clause is specified, the returned rows are sorted in the specified order. If ORDER BY is not given, the rows are returned in whatever order the system finds fastest to produce. See ORDER BY Clause below.

  9. If the LIMIT (or FETCH FIRST) or OFFSET clause is specified, the SELECT statement only returns a subset of the result rows. See LIMIT Clause below.


WITH Clause

The WITH clause allows you to specify one or more subqueries that can be referenced by name in the primary query. The subqueries effectively act as temporary tables or views for the duration of the primary query. Each subquery can be a SELECT, TABLE, or VALUES statement.

A name (without schema qualification) must be specified for each WITH query. Optionally, a list of column names can be specified; if this is omitted, the column names are inferred from the subquery.

If RECURSIVE is specified, it allows a SELECT subquery to reference itself by name. Such a subquery must have the form <non_recursive_term> UNION [ ALL | DISTINCT ] <recursive_term> where the recursive self-reference must appear on the right-hand side of the UNION. Only one recursive self-reference is permitted per query. Recursive data-modifying statements are not supported, but you can use the results of a recursive SELECT query in a data-modifying statement.

A key property of WITH queries is that they are evaluated only once per execution of the primary query, even if the primary query refers to them more than once. In particular, data-modifying statements are guaranteed to be executed once and only once, regardless of whether the primary query reads all or any of their output.

The primary query and the WITH queries are all (notionally) executed at the same time. This implies that the effects of a data-modifying statement in WITH cannot be seen from other parts of the query, other than by reading its RETURNING output. If two such data-modifying statements attempt to modify the same row, the results are unspecified.

FROM Clause

The FROM clause specifies one or more source tables for the SELECT. If multiple sources are specified, the result is the Cartesian product (cross join) of all the sources. But usually qualification conditions are added (via WHERE) to restrict the returned rows to a small subset of the Cartesian product.

The FROM clause can contain the following elements:

The name (optionally schema-qualified or database-qualified) of an existing table or view.
A substitute name for the FROM item containing the alias. An alias is used for brevity or to eliminate ambiguity for self-joins (where the same table is scanned multiple times). When an alias is provided, it completely hides the actual name of the table or function; for example given FROM foo AS f, the remainder of the SELECT must refer to this FROM item as f not foo. If an alias is written, a column alias list can also be written to provide substitute names for one or more columns of the table.
TABLESAMPLE sampling_method ( sample_size ) [ REPEATABLE ( seed ) ]
A TABLESAMPLE clause after a <table_name> indicates that the specified <sampling_method> should be used to retrieve a subset of the rows in that table. This sampling precedes the application of any other filters such as WHERE clauses. Hyper supports two sampling methods, BERNOULLI and SYSTEM.
The optional REPEATABLE clause specifies a <seed> number to use for generating random numbers within the sampling method. The seed value can be any non-null floating-point literal. Two queries that specify the same seed and <sample_size> values will select the same sample of the table, if the table has not been changed meanwhile. But different seed values will usually produce different samples. If REPEATABLE is not given then a new random sample is selected for each query, based upon a system-generated seed.
The BERNOULLI method scans the whole table and selects or ignores individual rows independently. The SYSTEM method does block-level sampling, i.e. tuples are drawn randomly in a subset of the table's data blocks. The SYSTEM method is significantly faster than the BERNOULLI method when small sampling percentages are specified, but it may return a less-random sample of the table as a result of clustering effects.
The BERNOULLI and SYSTEM sampling methods each accept a single <sample_size> argument which determines the number of rows to be sampled from the table. The sample size can be specified as a fixed number of rows using the ROWS syntax, or as a percentage (specified as a real number between 0 and 100) of the total number of rows in the table using the PERCENT syntax. If only a number is provided without any keywords, PERCENT is assumed as default. The argument used for the size must be a numeric literal.
When PERCENT is specified explicitly, the absolute number of rows returned can be bounded with an optional BETWEEN clause, which specifies the minimum and maximum number of rows to be returned. The UNBOUNDED keyword can be used instead of a number argument to indicate that the sample size is not bounded, either from below or from above. Specifying UNBOUNDED in both arguments is not valid.
Note that the lower bound is not guaranteed. If the table has too few rows, the sample might be smaller than the given lower bound with PERCENT or than the given row count with ROWS. Upper bounds, on the other hand, are guaranteed.
A sub-SELECT can appear in the FROM clause. This acts as though its output were created as a temporary table for the duration of this single SELECT command. Note that the sub-SELECT must be surrounded by parentheses, and providing an alias for it is optional. If an alias is not provided, the columns of the sub-query are only accessible if their names are unique, i.e., they do not conflict with the columns produced by any other source table in the FROM clause. Note that VALUES is also considered a SELECT; thus, it can also be used here.
A WITH query is referenced by writing its name, just as though the query's name were a table name. (In fact, the WITH query hides any real table of the same name for the purposes of the primary query. If necessary, you can refer to a real table of the same name by schema-qualifying the table's name.) An alias can be provided in the same way as for a table.
Function calls can appear in the FROM clause. (This is especially useful for functions that return result sets, but any function can be used.) This acts as though the function's output were created as a temporary table for the duration of this single SELECT command. An alias can be provided in the same way as for a table. If an alias is written, a column alias list can also be written to provide substitute names for one or more attributes of the function's composite return type.
For the INNER and OUTER join types, a join condition must be specified, namely exactly one of NATURAL, ON join_condition, or USING (join_column [, ...]). See below for the meaning. For CROSS JOIN, none of these clauses can appear.
A JOIN clause combines two FROM items, which for convenience we will refer to as "tables", though in reality they can be any type of FROM item. Use parentheses if necessary to determine the order of nesting. In the absence of parentheses, JOINs nest left-to-right. In any case JOIN binds more tightly than the commas separating FROM-list items.
CROSS JOIN and INNER JOIN produce a simple Cartesian product, the same result as you get from listing the two tables at the top level of FROM, but restricted by the join condition (if any). CROSS JOIN is equivalent to INNER JOIN ON (TRUE), that is, no rows are removed by qualification. These join types are just a notational convenience, since they do nothing you couldn't do with plain FROM and WHERE.
LEFT OUTER JOIN returns all rows in the qualified Cartesian product (i.e., all combined rows that pass its join condition), plus one copy of each row in the left-hand table for which there was no right-hand row that passed the join condition. This left-hand row is extended to the full width of the joined table by inserting null values for the right-hand columns. Note that only the JOIN clause's own condition is considered while deciding which rows have matches. Outer conditions are applied afterwards.
Conversely, RIGHT OUTER JOIN returns all the joined rows, plus one row for each unmatched right-hand row (extended with nulls on the left). This is just a notational convenience, since you could convert it to a LEFT OUTER JOIN by switching the left and right tables.
FULL OUTER JOIN returns all the joined rows, plus one row for each unmatched left-hand row (extended with nulls on the right), plus one row for each unmatched right-hand row (extended with nulls on the left).
ON <join_condition>
<join_condition> is an expression resulting in a value of type boolean (similar to a WHERE clause) that specifies which rows in a join are considered to match.
USING ( <join_column> [, ...] )
A clause of the form USING ( a, b, ... ) is shorthand for ON left_table.a = right_table.a AND left_table.b = right_table.b .... Also, USING implies that only one of each pair of equivalent columns will be included in the join output, not both.
NATURAL is shorthand for a USING list that mentions all columns in the two tables that have matching names. If there are no common column names, NATURAL is equivalent to ON TRUE.
The LATERAL keyword can precede a sub-SELECT or a function-call FROM item. In the SQL standard, LATERAL allows a sub-query or function call to access the attributes of preceding FROM items. In Hyper, sub-queries can always access the attributes of preceding FROM items, even if the LATERAL keyword is not specified. As such, this keyword has no effect in Hyper and it is kept just for compatibility reasons.

WHERE Clause

The optional WHERE clause has the general form WHERE <condition> where <condition> is any expression that evaluates to a result of type boolean. Any row that does not satisfy this condition will be eliminated from the output. A row satisfies the condition if it returns true when the actual row values are substituted for any variable references.


The optional GROUP BY clause has the general form GROUP BY <grouping_element> [, ...].

GROUP BY will condense into a single row all selected rows that share the same values for the grouped expressions. An <expression> used inside a grouping_element can be an input column name, or the name or ordinal number of an output column (SELECT list item), or an arbitrary expression formed from input-column values. In case of ambiguity, a GROUP BY name will be interpreted as an input-column name rather than an output column name.

If any of GROUPING SETS, ROLLUP or CUBE are present as grouping elements, then the GROUP BY clause as a whole defines some number of independent grouping sets. The effect of this is equivalent to constructing a UNION ALL between subqueries with the individual grouping sets as their GROUP BY clauses. The optional DISTINCT clause removes duplicate sets before processing; it does not transform the UNION ALL into a UNION DISTINCT. For further details on the handling of grouping sets see Grouping Sets.

Aggregate functions, if any are used, are computed across all rows making up each group, producing a separate value for each group. (If there are aggregate functions but no GROUP BY clause, the query is treated as having a single group comprising all the selected rows.)

When GROUP BY is present, or any aggregate functions are present, it is not valid for the SELECT list expressions to refer to ungrouped columns except within aggregate functions, since there would otherwise be more than one possible value to return for an ungrouped column.

Keep in mind that all aggregate functions are evaluated before evaluating any "scalar" expressions in the HAVING clause or SELECT list. This means that, for example, a CASE expression cannot be used to skip evaluation of an aggregate function.


The optional HAVING clause has the general form HAVING <condition> where <condition> is the same as specified for the WHERE clause.

HAVING eliminates group rows that do not satisfy the condition. HAVING is different from WHERE: WHERE filters individual rows before the application of GROUP BY, while HAVING filters group rows created by GROUP BY. Each column referenced in <condition> must unambiguously reference a grouping column, unless the reference appears within an aggregate function.

The presence of HAVING turns a query into a grouped query even if there is no GROUP BY clause. This is the same as what happens when the query contains aggregate functions but no GROUP BY clause. All the selected rows are considered to form a single group, and the SELECT list and HAVING clause can only reference table columns from within aggregate functions. Such a query will emit a single row if the HAVING condition is true, zero rows if it is not true.


The optional WINDOW clause has the general form

WINDOW <window_name> AS ( <window_definition> ) [, ...]

where <window_name> is a name that can be referenced from OVER clauses or subsequent window definitions, and <window_definition> is

[ <existing_window_name> ]
[ PARTITION BY <expression> [, ...] ]
[ ORDER BY `<expression>` [ ASC | DESC ] [ NULLS { FIRST | LAST } ] [, ...] ]
[ <frame_clause> ]

If an <existing_window_name> is specified it must refer to an earlier entry in the WINDOW list; the new window copies its partitioning clause from that entry, as well as its ordering clause if any. In this case the new window cannot specify its own PARTITION BY clause, and it can specify ORDER BY only if the copied window does not have one. The new window always uses its own frame clause; the copied window must not specify a frame clause.

The elements of the PARTITION BY list are interpreted in much the same fashion as elements of a GROUP BY Clause, except that they are always simple expressions and never the name or number of an output column. Another difference is that these expressions can contain aggregate function calls, which are not allowed in a regular GROUP BY clause. They are allowed here because windowing occurs after grouping and aggregation.

Similarly, the elements of the ORDER BY list are interpreted in much the same fashion as elements of an PRDER BY Clause, except that the expressions are always taken as simple expressions and never the name or number of an output column.

The optional <frame_clause> defines the window frame for window functions that depend on the frame (not all do). The window frame is a set of related rows for each row of the query (called the current row). The <frame_clause> can be one of

{ RANGE | ROWS } <frame_start> [ <frame_exclusion> ]
{ RANGE | ROWS } BETWEEN <frame_start> AND <frame_end> [ <frame_exclusion> ]

where <frame_start> and <frame_end> can be one of

<offset> PRECEDING
<offset> FOLLOWING

and <frame_exclusion> can be one of


If <frame_end> is omitted it defaults to CURRENT ROW. Restrictions are that <frame_start> cannot be UNBOUNDED FOLLOWING, <frame_end> cannot be UNBOUNDED PRECEDING.

The default framing option is RANGE UNBOUNDED PRECEDING, which is the same as RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW; it sets the frame to be all rows from the partition start up through the current row's last peer (a row that the window's ORDER BY clause considers equivalent to the current row; all rows are peers if there is no ORDER BY). In general, UNBOUNDED PRECEDING means that the frame starts with the first row of the partition, and similarly UNBOUNDED FOLLOWING means that the frame ends with the last row of the partition, regardless of RANGE or ROWS mode. In ROWS mode, CURRENT ROW means that the frame starts or ends with the current row; but in RANGE mode it means that the frame starts or ends with the current row's first or last peer in the ORDER BY ordering. The <offset> PRECEDING and <offset> FOLLOWING options vary in meaning depending on the frame mode. In ROWS mode, the <offset> is an integer indicating that the frame starts or ends that many rows before or after the current row. In RANGE mode, use of an <offset> option requires that there be exactly one ORDER BY column in the window definition. Then the frame contains those rows whose ordering column value is no more than <offset> less than (for PRECEDING) or more than (for FOLLOWING) the current row's ordering column value. In these cases the data type of the <offset> expression depends on the data type of the ordering column. For numeric ordering columns it is typically of the same type as the ordering column, but for datetime ordering columns it is an interval. In all these cases, the value of the <offset> must be non-null and non-negative. Also, while the <offset> does not have to be a simple constant, it cannot contain variables, aggregate functions, or window functions.

The <frame_exclusion> option allows rows around the current row to be excluded from the frame, even if they would be included according to the frame start and frame end options. EXCLUDE CURRENT ROW excludes the current row from the frame. EXCLUDE GROUP excludes the current row and its ordering peers from the frame. EXCLUDE TIES excludes any peers of the current row from the frame, but not the current row itself. EXCLUDE NO OTHERS simply specifies explicitly the default behavior of not excluding the current row or its peers.

Beware that the ROWS mode can produce unpredictable results if the ORDER BY ordering does not order the rows uniquely. The RANGE mode is designed to ensure that rows that are peers in the ORDER BY ordering are treated alike: all rows of a given peer group will be in the frame or excluded from it.

The purpose of a WINDOW clause is to specify the behavior of window functions appearing in the query's List or Clause. These functions can reference the WINDOW clause entries by name in their OVER clauses. A WINDOW clause entry does not have to be referenced anywhere, however; if it is not used in the query it is simply ignored. It is possible to use window functions without any WINDOW clause at all, since a window function call can specify its window definition directly in its OVER clause. However, the WINDOW clause saves typing when the same window definition is needed for more than one window function.

Window functions are described in detail in Window Functions and Queries.


The SELECT list (between the key words SELECT and FROM) specifies expressions that form the output rows of the SELECT statement. The expressions can (and usually do) refer to columns computed in the FROM clause.

Just as in a table, every output column of a SELECT has a name. In a simple SELECT this name is just used to label the column for display, but when the SELECT is a sub-query of a larger query, the name is seen by the larger query as the column name of the result set produced by the sub-query. To specify the name to use for an output column, write AS <output_name> after the column's expression. (You can omit AS, but only if the desired output name does not match any Hyper keyword). For protection against possible future keyword additions, it is recommended that you always either write AS or double-quote the output name.) If you do not specify a column name, a name is chosen automatically by Hyper. If the column's expression is a simple column reference then the chosen name is the same as that column's name. In more complex cases a function or type name may be used, or the system may fall back to a number that specifies the order of that column in the result set, starting from 1.

An output column's name can be used to refer to the column's value in ORDER BY and GROUP BY clauses, but not in the WHERE or HAVING clauses; there you must write out the expression instead.

Instead of an expression, * can be written in the output list as a shorthand for all the columns of the selected rows. Also, you can write table_name.* as a shorthand for the columns coming from just that table. In these cases it is not possible to specify new names with AS; the output column names will be the same as the table columns' names.

According to the SQL standard, the expressions in the output list should be computed before applying DISTINCT, ORDER BY, or LIMIT. This is obviously necessary when using DISTINCT, since otherwise it's not clear what values are being made distinct. However, in many cases it is convenient if output expressions are computed after ORDER BY and LIMIT; particularly if the output list contains anyexpensive functions. With that behavior, the order of function evaluations is more intuitive and there will not be evaluations corresponding to rows that never appear in the output. Hyper will effectively evaluate output expressions after sorting and limiting, so long as those expressions are not referenced in DISTINCT, ORDER BY or GROUP BY. (As a counterexample, SELECT f(x) FROM tab ORDER BY 1 clearly must evaluate f(x) before sorting.) Output expressions that contain set-returning functions are effectively evaluated after sorting and before limiting, so that LIMIT will act to cut off the output from a set-returning function.


If SELECT DISTINCT is specified, all duplicate rows are removed from the result set (one row is kept from each group of duplicates). SELECT ALL specifies the opposite: all rows are kept; that is the default.

SELECT DISTINCT ON ( expression [, ...] ) keeps only the first row of each set of rows where the given expressions evaluate to equal. The DISTINCT ON expressions are interpreted using the same rules as for ORDER BY (see above). Note that the "first row" of each set is unpredictable unless ORDER BY is used to ensure that the desired row appears first. For example:

SELECT DISTINCT ON (location) location, time, report
FROM weather_reports
ORDER BY location, time DESC;

retrieves the most recent weather report for each location. But if we had not used ORDER BY to force descending order of time values for each location, we'd have gotten a report from an unpredictable time for each location.

The DISTINCT ON expression(s) must match the leftmost ORDER BY expression(s). The ORDER BY clause will normally contain additional expression(s) that determine the desired precedence of rows within each DISTINCT ON group.

UNION Clause

The UNION clause has the general form


<select_statement> is any SELECT statement without an ORDER BY or LIMIT clause. (ORDER BY and LIMIT can be attached to a subexpression if it is enclosed in parentheses. Without parentheses, these clauses will be taken to apply to the result of the UNION, not to its right-hand input expression.)

The UNION operator computes the set union of the rows returned by the involved SELECT statements. A row is in the set union of two result sets if it appears in at least one of the result sets. The two SELECT statements that represent the direct operands of the UNION must produce the same number of columns, and corresponding columns must be of compatible data types.

The result of UNION does not contain any duplicate rows unless the ALL option is specified. ALL prevents elimination of duplicates. (Therefore, UNION ALL is usually significantly quicker than UNION; use UNION ALL when you can.) DISTINCT can be written to explicitly specify the default behavior of eliminating duplicate rows.

Multiple UNION operators in the same SELECT statement are evaluated left to right, unless otherwise indicated by parentheses.


The INTERSECT clause has the general form


<select_statement> is any SELECT statement without an ORDER BY or LIMIT clause.

The INTERSECT operator computes the set intersection of the rows returned by the involved SELECT statements. A row is in the intersection of two result sets if it appears in both result sets.

The result of INTERSECT does not contain any duplicate rows unless the ALL option is specified. With ALL, a row that has m duplicates in the left table and n duplicates in the right table will appear min(m, n) times in the result set. DISTINCT can be written to explicitly specify the default behavior of eliminating duplicate rows.

Multiple INTERSECT operators in the same SELECT statement are evaluated left to right, unless parentheses dictate otherwise. INTERSECT binds more tightly than UNION. That is, A UNION B INTERSECT C will be read as A UNION (B INTERSECT C).


The EXCEPT clause has the general form


<select_statement> is any SELECT statement without an ORDER BY or LIMIT clause.

The EXCEPT operator computes the set of rows that are in the result of the left SELECT statement but not in the result of the right one.

The result of EXCEPT does not contain any duplicate rows unless the ALL option is specified. With ALL, a row that has m duplicates in the left table and n duplicates in the right table will appear max(m - n, 0) times in the result set. DISTINCT can be written to explicitly specify the default behavior of eliminating duplicate rows.

Multiple EXCEPT operators in the same SELECT statement are evaluated left to right, unless parentheses dictate otherwise. EXCEPT binds at the same level as UNION.


The optional ORDER BY clause has the general form:

ORDER BY <expression> [ ASC | DESC ] [ NULLS { FIRST | LAST } ] [, ...]

The ORDER BY clause causes the result rows to be sorted according to the specified expression(s). If two rows are equal according to the leftmost expression, they are compared according to the next expression and so on. If they are equal according to all specified expressions, they are returned in an implementation-dependent order.

Each <expression> can be the name or ordinal number of an output column (SELECT list item), or it can be an arbitrary expression formed from input-column values.

The ordinal number refers to the ordinal (left-to-right) position of the output column. This feature makes it possible to define an ordering on the basis of a column that does not have a unique name. This is never absolutely necessary because it is always possible to assign a name to an output column using the AS clause.

It is also possible to use arbitrary expressions in the ORDER BY clause, including columns that do not appear in the SELECT output list. Thus the following statement is valid:

SELECT name FROM distributors ORDER BY code;

A limitation of this feature is that an ORDER BY clause applying to the result of a UNION, INTERSECT, or EXCEPT clause can only specify an output column name or number, not an expression.

If an ORDER BY expression is a simple name that matches both an output column name and an input column name, ORDER BY will interpret it as the output column name. This is the opposite of the choice that GROUP BY will make in the same situation. This inconsistency is made to be compatible with the SQL standard.

Optionally one can add the key word ASC (ascending) or DESC (descending) after any expression in the ORDER BY clause. If not specified, ASC is assumed by default.

If NULLS LAST is specified, null values sort after all non-null values; if NULLS FIRST is specified, null values sort before all non-null values. If neither is specified, the default behavior is NULLS LAST when ASC is specified or implied, and NULLS FIRST when DESC is specified (thus, the default is to act as though nulls are larger than non-nulls).

Note that ordering options apply only to the expression they follow; for example ORDER BY x, y DESC does not mean the same thing as ORDER BY x DESC, y DESC.

Character-string data is sorted according to the collation that applies to the column being sorted. That can be overridden at need by including a COLLATE clause in the <expression>, for example ORDER BY mycolumn COLLATE "en_US".


The LIMIT clause consists of two independent sub-clauses: LIMIT { <count> | ALL } OFFSET <start>. <count> specifies the maximum number of rows to return, while <start> specifies the number of rows to skip before starting to return rows. When both are specified, <start> rows are skipped before starting to count the <count> rows to be returned.

If the <count> expression evaluates to NULL, it is treated as LIMIT ALL, i.e., no limit. If <start> evaluates to NULL, it is treated the same as OFFSET 0.

SQL:2008 introduced a different syntax to achieve the same result, which Hyper also supports. It is:

OFFSET <start> { ROW \| ROWS }
FETCH { FIRST | NEXT } [ <count> ] { ROW | ROWS } { ONLY | WITH TIES }

In this syntax, the <start> or <count> value is required by the standard to be a literal constant, a parameter, or a variable name. If <count> is omitted in a FETCH clause, it defaults to 1. The WITH TIES option is used to return any additional rows that tie for the last place in the result set according to the ORDER BY clause. ROW and ROWS as well as FIRST and NEXT are noise words that don't influence the effects of these clauses. According to the standard, the OFFSET clause must come before the FETCH clause if both are present; but Hyper is laxer and allows either order.

When using LIMIT, it is a good idea to use an ORDER BY clause that constrains the result rows into a unique order. Otherwise you will get an unpredictable subset of the query's rows — you might be asking for the tenth through twentieth rows, but tenth through twentieth in what ordering? You don't know what ordering unless you specify ORDER BY.

The query planner takes LIMIT into account when generating a query plan, so you are very likely to get different plans (yielding different row orders) depending on what you use for LIMIT and OFFSET. Thus, using different LIMIT/OFFSET values to select different subsets of a query result will give inconsistent results unless you enforce a predictable result ordering with ORDER BY. This is not a bug; it is an inherent consequence of the fact that SQL does not promise to deliver the results of a query in any particular order unless ORDER BY is used to constrain the order.

It is even possible for repeated executions of the same LIMIT query to return different subsets of the rows of a table, if there is not an ORDER BY to enforce selection of a deterministic subset. Again, this is not a bug; determinism of the results is simply not guaranteed in such a case.


More complex grouping operations than those described above are possible using the concept of grouping sets. The data selected by the FROM and WHERE clauses is grouped separately by each specified grouping set, aggregates are computed for each group just as for simple GROUP BY clauses, and then the results are returned.

Each sublist of GROUPING SETS may specify zero or more columns or expressions and is interpreted the same way as though it were directly in the GROUP BY clause. An empty grouping set means that all rows are aggregated down to a single group (which is output even if no input rows were present), as described above for the case of aggregate functions with no GROUP BY clause.

References to the grouping columns or expressions are replaced by null values in result rows for grouping sets in which those columns do not appear. To distinguish which grouping a particular output row resulted from, use the GROUPING function.

A shorthand notation is provided for specifying two common types of grouping set. A clause of the form

ROLLUP ( e1, e2, e3, ... )

represents the given list of expressions and all prefixes of the list including the empty list; thus it is equivalent to

( e1, e2, e3, ... ),
( e1, e2 ),
( e1 ),
( )

This is commonly used for analysis over hierarchical data; e.g., total salary by department, division, and company-wide total.

A clause of the form

CUBE ( e1, e2, ... )

represents the given list and all of its possible subsets (i.e., the power set). Thus

CUBE ( a, b, c )

is equivalent to

( a, b, c ),
( a, b ),
( a, c ),
( a ),
( b, c ),
( b ),
( c ),
( )

CUBE is limited to at most 12 expressions.

The individual elements of a CUBE or ROLLUP clause may be either individual expressions, or sublists of elements in parentheses. In the latter case, the sublists are treated as single units for the purposes of generating the individual grouping sets. For example:

CUBE ( (a, b), (c, d) )

is equivalent to

( a, b, c, d ),
( a, b ),
( c, d ),
( )


ROLLUP ( a, (b, c), d )

is equivalent to

( a, b, c, d ),
( a, b, c ),
( a ),
( )

The CUBE and ROLLUP constructs can be used either directly in the GROUP BY clause, or nested inside a GROUPING SETS clause. If one GROUPING SETS clause is nested inside another, the effect is the same as if all the elements of the inner clause had been written directly in the outer clause.

If multiple grouping items are specified in a single GROUP BY clause, then the final list of grouping sets is the cross product of the individual items. For example:

GROUP BY a, CUBE (b, c), GROUPING SETS ((d), (e))

is equivalent to

(a, b, c, d), (a, b, c, e),
(a, b, d), (a, b, e),
(a, c, d), (a, c, e),
(a, d), (a, e)

When specifying multiple grouping items together, the final set of grouping sets might contain duplicates. For example:


is equivalent to

(a, b, c),
(a, b),
(a, b),
(a, c),
(a, c),

If these duplicates are undesirable, they can be removed using the DISTINCT clause directly on the GROUP BY. Therefore:


is equivalent to

(a, b, c),
(a, b),
(a, c),

This is not the same as using SELECT DISTINCT because the output rows may still contain duplicates. If any of the ungrouped columns contains NULL, it will be indistinguishable from the NULL used when that same column is grouped.


To join the table films with the table distributors:

SELECT f.title, f.did,, f.date_prod, f.kind
FROM distributors d, films f
WHERE f.did = d.did

title | did | name | date_prod | kind
The Third Man | 101 | British Lion | 1949-12-23 | Drama
The African Queen | 101 | British Lion | 1951-08-11 | Romantic

To sum the column len of all films and group the results by kind:

SELECT kind, sum(len) AS total FROM films GROUP BY kind;

kind | total
Action | 07:34
Comedy | 02:58
Drama | 14:28
Musical | 06:42
Romantic | 04:38

To sum the column len of all films, group the results by kind and show those group totals that are less than 5 hours:

SELECT kind, sum(len) AS total
FROM films
HAVING sum(len) < interval '5 hours';

kind | total
Comedy | 02:58
Romantic | 04:38

The following two examples are identical ways of sorting the individual results according to the contents of the second column (name):

SELECT * FROM distributors ORDER BY name;
SELECT * FROM distributors ORDER BY 2;

did | name
109 | 20th Century Fox
110 | Bavaria Atelier
101 | British Lion
107 | Columbia
102 | Jean Luc Godard
113 | Luso films
104 | Mosfilm
103 | Paramount
106 | Toho
105 | United Artists
111 | Walt Disney
112 | Warner Bros.
108 | Westward

The next example shows how to obtain the union of the tables distributors and actors, restricting the results to those that begin with the letter W in each table. Only distinct rows are wanted, so the key word ALL is omitted.

distributors:               actors:
did | name id | name
-----+-------------- ----+----------------
108 | Westward 1 | Woody Allen
111 | Walt Disney 2 | Warren Beatty
112 | Warner Bros. 3 | Walter Matthau
... ...

FROM distributors
FROM actors

Walt Disney
Walter Matthau
Warner Bros.
Warren Beatty
Woody Allen

The following example shows how to use a function in the FROM clause. Currently, Hyper does not support user-defined table functions, but some built-in table functions such as generate_series are supported.


This example shows how to use a simple WITH clause:

SELECT random() as x FROM generate_series(1, 3)


Notice that the WITH query was evaluated only once, so that we got two sets of the same three random values.

This example uses WITH RECURSIVE to find all subordinates (direct or indirect) of the employee Mary, and their level of indirectness, from a table that shows only direct subordinates:

WITH RECURSIVE employee_recursive(distance, employee_name, manager_name) AS (
SELECT 1, employee_name, manager_name
FROM employee
WHERE manager_name = 'Mary'
SELECT er.distance + 1, e.employee_name, e.manager_name
FROM employee_recursive er, employee e
WHERE er.employee_name = e.manager_name
SELECT distance, employee_name FROM employee_recursive;

Notice the typical form of recursive queries: an initial condition, followed by UNION, followed by the recursive part of the query. Be sure that the recursive part of the query will eventually return no tuples, or else the query will loop indefinitely.

This example shows the use of TABLESAMPLE when querying a table with a sequence of 100 integers. It uses the sampling method SYSTEM to retrieve 10% of the table's rows, but bounded to a maximum of 6 rows. Since the table has 100 rows and the percentage alone would yield 10 rows, the result is truncated to 6 rows. Using the REPEATABLE clause with the same argument guarantees that the same sample will be returned every time the command is executed, provided that the table is not modified in-between.


FROM Numbers

This example shows the use of GROUPING SETS to group by multiple sets of columns within a singly query (see Grouping Sets).

SELECT * FROM items_sold;

brand | size | sales
Foo | L | 10
Foo | M | 20
Bar | M | 15
Bar | L | 5

SELECT brand, size, sum(sales) FROM items_sold GROUP BY GROUPING SETS ((brand), (size), ());

brand | size | sum
Foo | | 30
Bar | | 20
| L | 15
| M | 35
| | 50


Of course, the SELECT statement is compatible with the SQL standard. But there are some extensions and some missing features.

Omitted FROM Clauses

Hyper allows one to omit the FROM clause. It has a straightforward use to compute the results of simple expressions:



Some other SQL databases cannot do this except by introducing a dummy one-row table from which to do the SELECT.

Note that if a FROM clause is not specified, the query cannot reference any database tables. For example, the following query is invalid:

SELECT distributors.* WHERE = 'Westward';

Empty SELECT Lists

The list of output expressions after SELECT can be empty, producing a zero-column result table. This is not valid syntax according to the SQL standard. Hyper allows it to be consistent with allowing zero-column tables. However, an empty list is not allowed when DISTINCT is used.

Omitting the AS Key Word

In the SQL standard, the optional key word AS can be omitted before an output column name whenever the new column name is a valid column name (that is, not the same as any reserved keyword). Hyper is slightly more restrictive: AS is required if the new column name matches any keyword at all, reserved or not. Recommended practice is to use AS or double-quote output column names, to prevent any possible conflict against future keyword additions.

In FROM items, both the standard and Hyper allow AS to be omitted before an alias that is an unreserved keyword. But this is impractical for output column names, because of syntactic ambiguities.

TABLESAMPLE Clause Restrictions

The TABLESAMPLE clause is currently accepted only on regular tables. According to the SQL standard it should be possible to apply it to any FROM item.

Function Calls in FROM

Hyper allows a function call to be written directly as a member of the FROM list. In the SQL standard it would be necessary to wrap such a function call in a sub-SELECT; that is, the syntax FROM func(...) alias is approximately equivalent to FROM (SELECT func(...)) alias.

Namespace Available to GROUP BY and ORDER BY

In the SQL-92 standard, an ORDER BY clause can only use output column names or numbers, while a GROUP BY clause can only use expressions based on input column names. Hyper extends each of these clauses to allow the other choice as well (but it uses the standard's interpretation if there is ambiguity). Hyper also allows both clauses to specify arbitrary expressions. Note that names appearing in an expression will always be taken as input-column names, not as output-column names.

SQL:1999 and later use a slightly different definition which is not entirely upward compatible with SQL-92. In most cases, however, Hyper will interpret an ORDER BY or GROUP BY expression the same way SQL:1999 does.


The clauses LIMIT and OFFSET are Hyper-specific syntax, also used by PostgreSQL. The SQL:2008 standard has introduced the clauses OFFSET ... FETCH {FIRST|NEXT} ... for the same functionality, as shown above in the LIMIT Clause.


DISTINCT ON ( ... ) is an extension of the SQL standard.